#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Modeling spatial variation in density of golden eagle nest sites in the western United States


Autoři: Jeffrey R. Dunk aff001;  Brian Woodbridge aff002;  Todd M. Lickfett aff003;  Geoffrey Bedrosian aff003;  Barry R. Noon aff004;  David W. LaPlante aff005;  Jessi L. Brown aff006;  Jason D. Tack aff007
Působiště autorů: Department of Environmental Science and Management, Humboldt State University, Arcata, CA, United States of America aff001;  U.S. Fish and Wildlife Service, Corvallis, Oregon, United States of America aff002;  U.S. Fish and Wildlife Service, Denver Federal Center, Denver, Colorado, United States of America aff003;  Department of Fish, Wildlife, and Conservation Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, United States of America aff004;  Natural Resource Geospatial, Montague, CA, United States of America aff005;  Department of Biology, University of Nevada Reno, Reno, NV, United States of America aff006;  U.S. Fish and Wildlife Service, Missoula, Montana, United States of America aff007
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0223143

Souhrn

In order to contribute to conservation planning efforts for golden eagles (Aquila chrysaetos) in the western U.S., we developed nest site models using >6,500 nest site locations throughout a >3,483,000 km2 area of the western U.S. We developed models for twelve discrete modeling regions, and estimated relative density of nest sites for each region. Cross-validation showed that, in general, models accurately estimated relative nest site densities within regions and sub-regions. Areas estimated to have the highest densities of breeding golden eagles had from 132–2,660 times greater densities compared to the lowest density areas. Observed nest site densities were very similar to those reported from published studies. Large extents of each modeling region consisted of low predicted nest site density, while a small percentage of each modeling region contained disproportionately high nest site density. For example, we estimated that areas with relative nest density values <0.3 represented from 62.8–97.8% (x¯ = 82.5%) of each modeling area, and those areas contained from 14.7–30.0% (x¯ = 22.1%) of the nest sites. In contrast, areas with relative nest density values >0.5 represented from 1.0–12.8% (x¯ = 6.3%) of modeling areas, and those areas contained from 47.7–66.9% (x¯ = 57.3%) of the nest sites. Our findings have direct application to: 1) large-scale conservation planning efforts, 2) risk analyses for land-use proposals such as recreational trails or wind power development, and 3) identifying mitigation areas to offset the impacts of human disturbance.

Klíčová slova:

Landforms – Habitats – Conservation science – California – Eagles – Deserts – Plateaus – Wind power


Zdroje

1. Gaston KJ, Fuller RA. The sizes of species’ geographic ranges. J Anim Ecol. 2009;46:1–9.

2. Wiens JD, Schumaker NH, Inman RD, Esque TC, Longshore KM, Nussear KE. Spatial demographic models to inform conservation planning of golden eagles in renewable energy landscapes. J Raptor Res. 2017;51:234–257. doi: 10.3356/JRR-16-77.1 30220786

3. Dunk JR, Woodbridge B, Schumaker N, White B, Glenn E, LaPlante DW, et al. Conservation planning for species recovery under the ndangered Species Act: a case study with the northern spotted owl. PLoS ONE. 2019;14(1): e0210643. doi: 10.1371/journal.pone.0210643 30640947

4. Fretwell SD. Populations in a seasonal environment. Monographs in population biology 5. Princeton, New Jersey: Princeton University Press; 1972.

5. Calsbeek R, Sinervo B. An experimental test of the ideal despotic distribution. J Anim Ecol. 2002;71:513–523.

6. Zimmerman GS, LaHaye WS, Gutierrez RJ. Empirical support for a despotic distribution in a California spotted owl population. Behav Ecol. 2003;14:433–437.

7. Village A. The home range and density of kestrels in relation to vole abundance. J Anim Ecol. 1982;51:413–428.

8. Village A. Numbers, territory-size and turnover of short-eared owls (Asio flammeus) in relation to vole abundance. Ornis Scandinavica. 1987;18:198–204.

9. Temeles EJ. The relative importance of prey availability and intruder pressure in feeding territory size regulation by harriers, Circus cyaneus. Oecologia. 1987;74:286–297. doi: 10.1007/BF00379372 28312003

10. Dunk JR, Cooper RJ. Territory-size regulation in black-shouldered kites. Auk. 1994;111:588–595.

11. Dugger KM, Forsman ED, Franklin AB, Davis RJ, White GC, Schwarz CJ, et al. The effects of habitat, climate, and barred owls on long-term demography of northern spotted owls. Condor. 2016;118: 57–116.

12. Kochert MN, Steenhof K, McIntyre CL, Craig EH. Golden eagle (Aquila chrysaetos). In: Rodewald PG, editor. The Birds of North America. Ithaca: Cornell Lab of Ornithology; 2002.

13. Braham M, Miller T, Duerr AE, Lanzone M, Fesnock A, LaPre L, et al. Home in the heat: dramatic seasonal variation in home range of desert golden eagles informs management of renewable energy development. Biol Conserv. 2015;186:225–232.

14. Hunt WG, Wiens JD, Law PR, Fuller MR, Hunt TL, Driscoll DE, et al. Quantifying the demographic cost of human-related mortality to a raptor population. PLoS ONE. 2017;12(2): e0172232. doi: 10.1371/journal.pone.0172232 28234926

15. Millsap BA, Grubb TG, Murphy RD, Swem T, Watson JW. Conservation significance of alternative nests of golden eagles. Glob Ecol Conserv. 2015;3:234–241.

16. McIntyre CL, Douglas DC, Collopy MW. Movements of golden eagles (Aquila chrysaetos) from interior Alaska during their first year of independence. The Auk. 2008;125: 214–224.

17. Bedrosian BE, Domenech R, Shreading A, Hayes MM, Booms TL, Barger CR. Migration corridors of adult golden eagles originating in northwestern North America. PloS ONE. 2018;13(11), e0205204. doi: 10.1371/journal.pone.0205204 30462652

18. Murphy RK, Dunk JR, Jacobsen K, LaPlante D, Millsap B, Woodbridge B, et al. First year dispersal of golden eagles from natal areas in the southwestern United States and implications for second-year settling. J Raptor Res. 2017;51:216–233.

19. US Fish and Wildlife Service. Bald and golden eagles: population demographics and estimation of sustainable take in the United States, 2016 update. US Department of the Interior, Fish and Wildlife Service, Washington, DC, U.S.A. 2016.

20. Collopy MW, Woodbridge B, Brown JL. Golden eagles in a changing world. J Raptor Res. 2017;51:193–197.

21. Kochert MN, Steenhof K, Carpenter LB, Marzluff JM. Effects of fire on golden eagle territory occupancy and reproductive success. J Wildl Manage. 1999;63:773–780.

22. Millsap BA, Zimmerman GS, Sauer SR, Neilson RM, Otto M, Bjerre E, et al. Golden eagle population trends in the western United States: 1968–2010. J Wildl Manage. 2013;77:1436–1448.

23. Pagel JE, Kritz KJ, Millsap BA, Murphy RK. Bald eagle and golden eagle mortalities at wind energy facilities in the contiguous United States. J Raptor Res. 2013;47:311–315.

24. Spaul RJ, Heath JA. Nonmotorized recreation and motorized recreation in shrub-steppe habitats affects behavior and reproduction of golden eagles (Aquila chrysaetos). Ecol Evol. 2016;6:8037–8049. doi: 10.1002/ece3.2540 27878076

25. Herring G, Eagle-Smith CA, Buck J. Characterizing golden eagle risk to lead and anticoagulant rodenticide exposure: a review. J Raptor Res. 2017;51: 273–292.

26. Mojica EK, Dwyer JF, Harness RE, Williams GE, Woodbridge B. Review and synthesis of research investigating Golden Eagle electrocutions. J Wildl Manage. 2018;82:495–506.

27. Bedrosian G, Carlisle JD, Woodbridge B, Dunk JR, Wallace ZP, Dwyer JF, et al. A spatially-explicit model to predict the relative risk of Golden Eagle electrocutions. J Raptor Res. Forthcoming 2020.

28. Olson LE, Oakleaf RJ, Squires JR, Wallace ZP, Kennedy PL. Nesting pair density and abundance of ferruginous hawks (Buteo regalis) and golden eagles (Aquila chrysaetos) from aerial surveys in Wyoming. J Raptor Res. 2015;49:400–412.

29. Wiens JD, Kolar PS, Hunt WG, Hunt T, Fuller MR, Bell DA. Spatial patterns in occupancy and reproduction of golden eagles during drought: prospects for conservation in changing environments. The Condor: Ornithological Applications. 2018;120:106–124.

30. Guisan A, Tingley R, Baumgartner JB, Naujokaitis‐Lewis I, Sutcliffe PR, Tulloch AI, et al. Predicting species distributions for conservation decisions. Ecol Lett. 2013;16:1424–1435. doi: 10.1111/ele.12189 24134332

31. Margules CR, Pressey RL. Systematic conservation planning. Nature. 2000;405:243–253. doi: 10.1038/35012251 10821285

32. Duflot R, Avon C, Roche P, Berges L. Combining habitat suitability models and spatial graphs for more effective landscape conservation planning: an applied methodological framework and a species case study. J Nat Conserv. 2018;46:38–47.

33. Bosso L, Smeraldo S, Rapuzzi P, Sama G, Garonna AP, Russo D. Nature protection areas of Europe are insufficient to preserve the threatened beetle Rosalia alpina (Coleaoptera: Cerambycida): evidence from species distribution models and conservation gap analysis. Ecol Entomol. 2018;43:192–203.

34. Adhikari D, Tiwary R, Singh PP, Upadhaya K, Singh B, Haridasan KE, et al. Ecological niche modeling as a cumulative environmental impact assessment tool for biodiversity assessment and conservation planning: a case study of critically endangered plan Lagerstroemia minuticapra in the Indian Eastern Himalaya. J Environ Manage. 2019;243:299–307. doi: 10.1016/j.jenvman.2019.05.036 31102897

35. Phillips SJ, Anderson RP, Schapire RE. Maximum entropy modeling of species geographic distributions. Ecological Modeling. 2006;190:231–259.

36. Warton DI, Shepherd LC. Poisson point process models solve the “pseudo-absence problem” for presence-only data in ecology. Ann Appl Stat. 2010;4:1383–1402.

37. Aarts G, MacKenzie M, McConnel B, Fedak M, Matthiopoulos J. Estimating space-use and habitat preference from wildlife telemetry data. Ecography. 2008;31:14–160.

38. Fithian W, T. Hastie. Finite-sample equivalence in statistical models for presence-only data. Ann Appl Stat. 2013;7:1917–1939. doi: 10.1214/13-AOAS667 25493106

39. Renner IW, Warton DI. Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology. Biometrics. 2013; 69:274–281. doi: 10.1111/j.1541-0420.2012.01824.x 23379623

40. Dudík M, Phillips SJ, Schapire RE. Performance guarantees for regularized maximum entropy density estimation. Proceedings of the Seventeenth Annual Conference on Computational Learning Theory; 2004. New York: ACM Press; 2004. p. 655–662.

41. Aarts G, Fieberg J, Matthiopoulos J. Comparative interpretation of count, presence-absence, and point methods for species distribution models. Methods Ecol Evol. 2012;3:177–187.

42. Boyce MS, Vernier PR, Nielsen SE, Schmiegelow FKA. Evaluating resource selection functions. Ecol Modell. 2002;157:281–300.

43. Kremen C, Cameron A, Moilanen A, Phillips SJ, Thomas CD, Beentje B, et al. Aligning conservation priorities across taxa in Madagascar with high-resolution planning tools. Science. 2008;320:222–226. doi: 10.1126/science.1155193 18403708

44. Carroll C, Dunk JR, Moilanen A. Optimizing resiliency of multi-species reserve networks to climate change in the Pacific Northwest, USA. Glob Chang Biol. 2010;16:891–904.

45. Tack JD, Fedy BC. Landscapes for energy and wildlife: conservation prioritization for golden eagles across large spatial scales. PLoS One. 2015;10(8) e0134781. doi: 10.1371/journal.pone.0134781 26262876

46. Dunk JR, Van Gelder-Hawley JJ. Red tree vole habitat suitability modeling: implications for conservation and management. For Ecol Manage. 2009;258:626–634.

47. Zielinski WJ, Dunk JR, Gray AN. Estimating habitat value using forest inventory data: the fisher (Martes pennanti) in northwestern California. For Ecol Manage. 2012;275:35–42.

48. Commission for Environmental Cooperation. North American Terrestrial Ecoregions—Level III. Background paper (metadata for electronic information product). 2011. Available from: http://www3.cec.org/islandora/en/item/10415-north-american-terrestrial-ecoregionslevel-iii-en.pdf.

49. Bedrosian G, Watson JW, Steenhof K, Kochert MN, Preston CR, Woodbridge B, et al. Spatial and temporal patterns in golden eagle diets in the western United States, with implications for conservation planning. J Raptor Res. 2017;51:347–368.

50. Postupalsky S. Raptor reproductive success: some problem with methods, criteria and terminology. In: Hamerstrom FN Jr., Harrell BE, Oldendorff RR, editors. Management of raptors. Vermillion: Raptor Research Foundation; 1974. p. 21–31.

51. Steenhof K, Kochert MN, McIntyre CL, Brown JL. Coming to terms about describing golden eagle reproduction. J Raptor Res. 2017;51:378–390.

52. Watson JW, Duff AA, Davies RW. Home range and resource selection by GPS-monitored adult golden eagles in the Columbia Plateau Ecoregion: implications for wind power development. J Wildl Manage. 2014;78: 1012–1021.

53. Kochert MN, Steenhof K. Frequency of nest use by golden eagles in southwestern Idaho. J Raptor Res. 2012;46:239–248.

54. Phillips SJ, Dudík M, Elith J, Graham CH, Lehmann A, Leathwick J, Ferrier S. Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecol Appl. 2009;19:181–197. doi: 10.1890/07-2153.1 19323182

55. Warren DL, Seifert SN. Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. Ecol Appl. 2011;21:335–342. doi: 10.1890/10-1171.1 21563566

56. Cao Y, DeWalt RE, Robinson JL, Tweddale T, Hinz L, Pessino M. Using Maxent to model the historic distributions of stonefly species in Illinois streams: the effects of regularization and threshold selections. Ecol Modell. 2013;259:30–39.

57. Hirzel AH, Le Lay G, Helfer V, Randin C, Guisan A. 2006. Evaluating the ability of habitat suitability models to predict species presences. Ecol Modell. 2006;199:142–152.

58. Cleland DT, Freeouf JA, Keys JE Jr., Nowacki GJ, Carpenter C, McNab WH. Ecological sub-regions: sections and subsections of the conterminous United States [1:3,500,000] [CD-ROM]. Sloan, A.M., cartog. Gen. Tech. Report WO-76. Washington, DC: Department of Agriculture, Forest Service; 2007.

59. Doherty KE, Evans JS, Coates PS, Juliusson LM, Fedy BC. Importance of regional variation in conservation planning: a rangewide example of the greater sage‐grouse. Ecosphere. 2016;7(10). doi: 10.1002/ecs2.1515

60. Watson J, Whitfield P. A Conservation Framework for the golden eagle (Aquila chrysaetos) in Scotland. J Raptor Res. 2002;36(1 Supplement):41–49.

61. Whitfield DP, Fielding AH, McLeod DR, Haworth P F, Watson J. A conservation framework for the golden eagle in Scotland: refining condition targets and assessment of constraint influences. Biol Conserv. 2006;130:465–480.

62. Crandall RH, Bedrosian BE, Craighead D. Habitat selection and factors influencing nest survival of golden eagles in south-central Montana. J Raptor Res. 2015;49:413–429.

63. McLeod DR, Whitfield DP, Fielding AH, Haworth PF, McGrady MJ. Predicting home range use by golden eagles Aquila chrysaetos in western Scotland. Avian Science. 2002;2:183–198.

64. LeBeau CW, Nielson RM, Hallingstad EC, Young DP. Daytime habitat selection by resident golden eagles (Aquila chrysaetos) in southern Idaho, USA. J Raptor Res. 2015;49:29–43.

65. Marzluff JM, Knick ST, KeKasy MS, Schueck LS, Zarriello TJ. Spatial use and habitat selection of golden eagles in southwestern Idaho. Auk. 1997;114:673–687.

66. Guillera-Arroita G, Lahoz-Monfort JJ, Elith J, Gordon A, Kujala H, Lentini PE, et al. Is my species distribution model fit for purpose? Matching data and models to applications. Glob Ecol Biogeogr. 2015;24:276–292.

67. Royle JA, Chandler RB, Yuckulic C, and Nichols JD. Likelihood analysis of species occurrence probability from presence-only data for modeling species distributions. Methods Ecol Evol. 2012; 3:545–554.

68. Halvorsen R. A gradient analytic perspective on distribution modeling. Sommerfeltia. 2012;35:1–165.

69. Fedy BC, Doherty KE, Aldridge CL, O'Donnell M, Beck JL, Bedrosian B, et al. Habitat prioritization across large landscapes, multiple seasons, and novel areas: an example using greater sage-grouse in Wyoming. Wildlife Monographs. 2014;190:1–39.

70. Fargione J, Kiesecker J, Slaats MJ, Olimb S. Wind and wildlife in the Northern Great Plains: identifying low-impact areas for wind development. PLoS One. 2012;7(7), e41468. doi: 10.1371/journal.pone.0041468 22848505

71. US Fish and Wildlife Service. Eagle conservation plan guidance. Module 1–land-based wind energy. Version 2. Washington, DC: Department of Interior; 2013.

72. Tegen S, Lantz E, Mai T, Heimiller D, Hand M, Ibanez E. An Initial Evaluation of Siting Considerations on Current and Future Wind Deployment (No. NREL/TP-5000-61750). Golden: National Renewable Energy Lab (NREL); 2016.

73. Fish US and Service Wildlife. Greater Sage-Grouse: facts, figures and discussion: fact sheet. 2015. Available from: https://www.fws.gov/greatersagegrouse/factsheets/GreaterSageGrouseCanon_FINAL.pdf

74. US Fish and Wildlife Service. Final Programmatic Environmental Impact Statement for the Eagle Rule Revision. Washington, DC: US Department of the Interior; 2016.

75. Carlisle JD, Bedrosian G, McDonald TL. The influence of Greater Sage-Grouse management on risks faced by Golden Eagles in sagebrush ecosystems: a spatially explicit assessment of the umbrella species concept. Laramie: Western EcoSystems Technology, Inc.; 2017. Available from: https://ecos.fws.gov/ServCat/Reference/Profile/84851

76. Rowland MM, Wisdom MJ, Suring LH, Meinke CW. Greater sage-grouse as an umbrella species for sagebrush-associated vertebrates. Biol Conserv 2006;129:323–335.

77. Carlisle JD, Keinath DA, Albeke SE, Chalfoun AD. Identifying holes in the greater sage-grouse conservation umbrella. J Wildl Manage. 2018;82(5):948–957.

78. Baruch-Mordo S, Evans JS, Severson JP, Naugle DE, Maestas JD, Kiesecker JM, et al. Saving sage-grouse from the trees: a proactive solution to reducing a key threat to a candidate species. Biol Conserv. 2013;167:233–241.

79. Donnelly JP, Tack JD, Doherty KE, Naugle DE, Allred BW, Dreitz VJ. Extending conifer removal and landscape protection strategies from sage-grouse to songbirds, a range-wide assessment. Rangel Ecol Manag. 2017;70:95–105.

80. Fedy BC, Doherty KE. Population cycles are highly correlated over long time series and large spatial scales in two unrelated species: greater sage-grouse and cottontail rabbits. Oecologia. 2011;165:915–924. doi: 10.1007/s00442-010-1768-0 20848136

81. Dwyer JF, Harness RE, Eccleston D. Avian electrocutions on incorrectly retrofitted power poles. J Raptor Res. 2016;51:293–304.

82. Dunning JB, Stewart DJ, Danielson BJ, Noon BR, Root TL, Lamberson RH, et al. Spatially explicit population models: current forms and future uses. Ecol Appl. 1995;5(1):3–11.

83. Schumaker NH, Brookes A, Dunk JR, Woodbridge B, Heinrichs JA, Lawler J, et al. Mapping sources, sinks and connectivity using a simulation model of northern spotted owls. Landsc Ecol. 2014;29:579–592.

84. New L, Bjerre E, Millsap B, Otto MC, Runge MC. A collision risk model to predict avian fatalities at wind facilities: an example using golden eagles, Aquila chrysaetos. PLoS ONE 2015;10(7): e0130978. doi: 10.1371/journal.pone.0130978 26134412


Článok vyšiel v časopise

PLOS One


2019 Číslo 9
Najčítanejšie tento týždeň
Najčítanejšie v tomto čísle
Kurzy

Zvýšte si kvalifikáciu online z pohodlia domova

Získaná hemofilie - Povědomí o nemoci a její diagnostika
nový kurz

Eozinofilní granulomatóza s polyangiitidou
Autori: doc. MUDr. Martina Doubková, Ph.D.

Všetky kurzy
Prihlásenie
Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.

Prihlásenie

Nemáte účet?  Registrujte sa

#ADS_BOTTOM_SCRIPTS#